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Publication numberUS7272531 B2
Publication typeGrant
Application numberUS 11/230,855
Publication dateSep 18, 2007
Filing dateSep 20, 2005
Priority dateSep 20, 2005
Fee statusPaid
Also published asCN101268427A, CN101268427B, EP1938165A1, EP1938165B1, US20070067142, WO2007035205A1
Publication number11230855, 230855, US 7272531 B2, US 7272531B2, US-B2-7272531, US7272531 B2, US7272531B2
InventorsKadir Kavaklioglu, Steven R. Dillon, Gregory H. Rome, Jon Westbrock
Original AssigneeFisher-Rosemount Systems, Inc.
Export CitationBiBTeX, EndNote, RefMan
External Links: USPTO, USPTO Assignment, Espacenet
Aggregation of asset use indices within a process plant
US 7272531 B2
Abstract
A method of monitoring an entity within a process plant wherein the entity includes a plurality of lower level entities, includes acquiring a plurality of use indices, acquiring a plurality of weighting values, and creating an aggregate use index from a combination of the lower level use indices and weighting values, wherein the aggregate use index represents status information regarding the entity. Each use index pertains to status information regarding one of the plurality of lower level entities, and each weighting value pertains to the importance of a lower level entity among the plurality of lower level entities.
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Claims(71)
1. A method of monitoring an entity within a process plant wherein the entity includes a plurality of lower level entities, the method comprising:
acquiring a plurality of use indices, each use index pertaining to status information regarding one of the plurality of lower level entities;
acquiring a plurality of weighting values, each weighting value pertaining to the importance of a lower level entity among the plurality of lower level entities, and wherein each weighting value is based on the impact of the lower level entity on the entity and the frequency of failure of the lower level entity;
creating an aggregate use index from a combination of the lower level use indices and weighting values, wherein the aggregate use index represents status information regarding the entity; and
storing the aggregate use index in a computer readable medium.
2. The method of claim 1, wherein each use index comprises a use index created from data pertaining to the operation of the lower level entity.
3. The method of claim 1, wherein the weighting value comprises the product of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity.
4. The method of claim 1, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on maintenance data pertaining to the lower level entity.
5. The method of claim 1, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on process data pertaining to the lower level entity.
6. The method of claim 1, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on diagnostic data pertaining to the lower level entity.
7. The method of claim 1, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on on-line monitoring data pertaining to the lower level entity.
8. The method of claim 1, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on heuristic data pertaining to the lower level entity.
9. The method of claim 1, wherein the weighting value pertains to the criticality of the lower level entity to the entity.
10. The method of claim 1, wherein the aggregate use index is an aggregate health index indicating the health of the entity.
11. The method of claim 1, wherein the aggregate use index is an aggregate performance index indicating the relative performance of the entity.
12. The method of claim 1, wherein the aggregate use index is an aggregate variability index indicating an amount of deviation of a parameter of the entity.
13. The method of claim 1, wherein the aggregate use index is an aggregate utilization index indicating a degree of exploitation of the entity.
14. The method of claim 1, wherein creating an aggregate use index comprises creating a weighted average of the use indices of the lower level entities.
15. The method of claim 1, wherein creating an aggregate use index comprises:
combining the weighting value of a lower level entity with the use index of the lower level entity to produce a combined value for each of the plurality of entities; and
summing the combined values for each of the plurality of lower level entities to produce a summed value;
dividing the summed value by the sum of the plurality of weighting values.
16. The method of claim 1, wherein creating the aggregate use index comprises computing the aggregate use index as:
u = i = 1 n w i u i i = 1 n w i
wherein:
u=the aggregate use index of the higher level entity
n=the number of lower level entities within the plurality of
entities
ui=the use index of the ith lower level entity
wi=the weighting value of the ith lower level entity.
17. A method of monitoring an entity within a process plant wherein the entity includes a plurality of lower level entities, the method comprising:
acquiring a plurality of use indices, each use index pertaining to status information regarding one of the plurality of lower level entities;
acquiring a plurality of weighting values, each weighting value pertaining to the importance of a lower level entity among the plurality of lower level entities and wherein a range of values for the weighting value is the same among each of the plurality of lower level entities;
creating an aggregate use index from a combination of the lower level use indices and weighting values, wherein the aggregate use index represents status information regarding the entity; and
storing the aggregate use index in a computer readable medium.
18. The method of claim 17, wherein each use index comprises a use index created from data pertaining to the operation of the lower level entity.
19. The method of claim 17, wherein the weighting value is based on the impact of the lower level entity on the entity and the frequency of failure of the lower level entity.
20. The method of claim 19, wherein the weighting value comprises the product of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity.
21. The method of claim 19, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on maintenance data pertaining to the lower level entity.
22. The method of claim 19, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on process data pertaining to the lower level entity.
23. The method of claim 19, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on diagnostic data pertaining to the lower level entity.
24. The method of claim 19, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on on-line monitoring data pertaining to the lower level entity.
25. The method of claim 19, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on heuristic data pertaining to the lower level entity.
26. The method of claim 17, wherein the weighting value pertains to the criticality of the lower level entity to the entity.
27. The method of claim 17, wherein the range of values for the use indices for each of the plurality of lower level entities is the same among each of the plurality of lower level entities.
28. The method of claim 17, wherein the aggregate use index is an aggregate health index indicating the health of the entity.
29. The method of claim 17, wherein the aggregate use index is an aggregate performance index indicating the relative performance of the entity.
30. The method of claim 17, wherein the aggregate use index is an aggregate variability index indicating an amount of deviation of a parameter of the entity.
31. The method of claim 17, wherein the aggregate use index is an aggregate utilization index indicating a degree of exploitation of the entity.
32. The method of claim 17, wherein creating an aggregate use index comprises creating a weighted average of the use indices of the lower level entities.
33. The method of claim 17, wherein creating an aggregate use index comprises:
combining the weighting value of a lower level entity with the use index of the lower level entity to produce a combined value for each of the plurality of entities; and
summing the combined values for each of the plurality of lower level entities to produce a summed value;
dividing the summed value by the sum of the plurality of weighting values.
34. The method of claim 17, wherein creating the aggregate use index comprises computing the aggregate use index as:
u = i = 1 n w i u i i = 1 n w i
wherein:
u=the aggregate use index of the higher level entity
n=the number of lower level entities within the plurality of
entities
ui=the use index of the ith lower level entity
wi=the weighting value of the ith lower level entity.
35. A method of monitoring an entity within a process plant wherein the entity includes a plurality of lower level entities, the method comprising:
acquiring a plurality of use indices, each use index pertaining to status information regarding one of the plurality of lower level entities, and wherein the range of values for the use indices for each of the plurality of lower level entities is the same among each of the plurality of lower level entities;
acquiring a plurality of weighting values, each weighting value pertaining to the importance of a lower level entity among the plurality of lower level entities and;
creating an aggregate use index from a combination of the lower level use indices and weighting values, wherein the aggregate use index represents status information regarding the entity; and
storing the aggregate use index in a computer readable medium.
36. The method of claim 35, wherein each use index comprises a use index created from data pertaining to the operation of the lower level entity.
37. The method of claim 35, wherein the weighting value is based on the impact of the lower level entity on the entity and the frequency of failure of the lower level entity.
38. The method of claim 37, wherein the weighting value comprises the product of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity.
39. The method of claim 37, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on maintenance data pertaining to the lower level entity.
40. The method of claim 37, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on process data pertaining to the lower level entity.
41. The method of claim 37, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on diagnostic data pertaining to the lower level entity.
42. The method of claim 37, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on on-line monitoring data pertaining to the lower level entity.
43. The method of claim 37, wherein at least one of the impact of the lower level entity on the entity and the frequency of failure of the lower level entity is based on heuristic data pertaining to the lower level entity.
44. The method of claim 35, wherein the weighting value pertains to the criticality of the lower level entity to the entity.
45. The method of claim 35, wherein a range of values for the weighting value is the same among each of the plurality of lower level entities.
46. The method of claim 35, wherein the aggregate use index is an aggregate health index indicating the health of the entity.
47. The method of claim 35, wherein the aggregate use index is an aggregate performance index indicating the relative performance of the entity.
48. The method of claim 35, wherein the aggregate use index is an aggregate variability index indicating an amount of deviation of a parameter of the entity.
49. The method of claim 35, wherein the aggregate use index is an aggregate utilization index indicating a degree of exploitation of the entity.
50. The method of claim 35, wherein creating an aggregate use index comprises creating a weighted average of the use indices of the lower level entities.
51. The method of claim 35, wherein creating an aggregate use index comprises:
combining the weighting value of a lower level entity with the use index of the lower level entity to produce a combined value for each of the plurality of entities; and
summing the combined values for each of the plurality of lower level entities to produce a summed value;
dividing the summed value by the sum of the plurality of weighting values.
52. The method of claim 35, wherein creating the aggregate use index comprises computing the aggregate use index as:
u = i = 1 n w i u i i = 1 n w i
wherein:
u=the aggregate use index of the higher level entity
n=the number of lower level entities within the plurality of
entities
ui=the use index of the ith lower level entity
wi=the weighting value of the ith lower level entity.
53. A method of monitoring an entity within a process plant, wherein the process plant comprises a system hierarchy having a plurality of levels and a plurality of devices, the method comprising:
acquiring a plurality of use indices, each use index pertaining to the status of a device;
assigning a weighting value to each device, the weighting value pertaining to the priority of the device among the plurality of devices, and wherein the weighting value is based on the impact of the device among the plurality of devices and the frequency of failure of the device;
combining the use index and weighting values assigned to each of the devices; and
creating an aggregate use index at each level of the system hierarchy from the combined use indices and weighting values; and
storing the aggregate use index in a computer readable medium.
54. The method of claim 53, wherein acquiring a use index pertaining to the status of each device comprises periodically acquiring a use index from each device.
55. The method of claim 53, wherein each use index comprises a use index created from data pertaining to the operation of the device.
56. The method of claim 53, further comprising creating a use index for each device based upon data pertaining to the operation of each of the plurality of entities while each entity is in operation.
57. The method of claim 53, wherein the aggregate use index comprises a weighted average of the plurality of use indices.
58. The method of claim 53, wherein creating an aggregate use index at each level of the system hierarchy from the combined use indices and weighting values comprises utilizing a weighted sum of the use indices and the weighting values.
59. The method of claim 53, wherein creating an aggregate use index at each level of the system hierarchy from the combined use indices and weighting values comprises utilizing a weighted average of the lower level use indices.
60. The method of claim 53, wherein the use index is a performance index indicating the relative performance of the device.
61. The method of claim 53, wherein the use index is a variability index indicating an amount of deviation of a parameter of the device.
62. The method of claim 53, wherein the use index is a utilization index indicating a degree of exploitation of the device.
63. The method of claim 53, wherein the use index is a health index indicating the health of the device.
64. The method of claim 53, further comprising displaying the aggregate use index for at least one level of hierarchy of the system hierarchy.
65. A system for displaying an aggregate use indices for a process plant having a plurality of entities, the system comprising:
a processor;
a display;
a database adapted to store use indices for each of the plurality of entities, each use index pertaining to the status of the entity and adapted to store weighting values for each of the plurality of entities, each weighting value pertaining to the importance of the entity among the plurality of entities, and wherein each weighting value is based on the impact of the entity on the higher level entity and the frequency of failure of the entity;
a routine adapted to be executed by the processor which stores a representation corresponding to a higher level entity plurality of entities in the database, the higher level entity comprises the plurality of entities;
a routine adapted to be executed by the processor which generates an aggregate use index from a combination of the plurality of use indices and the plurality of weighting values, the aggregate use index pertaining to the status of the higher level entity; and
a routine adapted to be executed by the processor which displays the representation and which displays the aggregate use index proximately to the corresponding representation.
66. The system of claim 65, wherein the aggregate use index comprises a weighted average of the product of each use index and each weighting value.
67. The system of claim 65, wherein the aggregate use index comprises a performance index indicating the relative performance of the higher level entity.
68. The system of claim 65, wherein the aggregate use index comprises a variability index indicating an amount of deviation of a parameter of the higher level entity.
69. The system of claim 65, wherein the aggregate use index comprises a utilization index indicating a degree of exploitation of the higher level entity.
70. The system of claim 65, wherein the aggregate use index comprises a health index indicating the health of the higher level entity.
71. The system of claim 65, wherein the representation of the higher level entity is a representation of the process plant.
Description
FIELD OF TECHNOLOGY

The present invention relates generally to process control systems within process plants and, more particularly, to the index aggregation to determine indices at varying levels of hierarchy within and among process plants.

DESCRIPTION OF THE RELATED ART

Process control systems, like those used in chemical, petroleum or other processes, typically include one or more centralized or decentralized process controllers communicatively coupled to at least one host or operator workstation and to one or more process control and instrumentation devices, such as field devices, via analog, digital or combined analog/digital buses. Field devices, which may be, for example valves, valve positioners, switches, transmitters, and sensors (e.g., temperature, pressure and flow rate sensors), perform functions within the process such as opening or closing valves and measuring process parameters. The process controller receives signals indicative of process measurements or process variables made by or associated with the field devices and/or other information pertaining to the field devices, uses this information to implement a control routine and then generates control signals which are sent over one or more of the buses to the field devices to control the operation of the process. Information from the field devices and the controller is typically made available to one or more applications executed by an operator workstation to enable an operator to perform desired functions with respect to the process, such as viewing the current state of the process, modifying the operation of the process, etc.

While a typical process control system has many process control and instrumentation devices, such as valves, transmitters, sensors, etc. connected to one or more process controllers which execute software that controls these devices during the operation of the process, there are many other supporting devices which are also necessary for or related to process operation. These additional devices include, for example, power supply equipment, power generation and distribution equipment, rotating equipment such as turbines, etc., which are located at numerous places in a typical plant.

The various devices within the process plant may be interconnected in physical and/or logical groups to create a logical process, such as a control loop. Likewise, a control loop may be interconnected with other control loops and/or devices to create sub-units. A sub-unit may be interconnected with other sub-units to create a unit, which in turn, may be interconnected with other units to create an area. Process plants generally include interconnected areas, and business entities generally include process plants which may be interconnected. As a result, a process plant includes numerous levels of hierarchy having interconnected assets, and a business enterprise may include interconnected process plants. In other words, assets related to a process plant, or process plants themselves, may be grouped together to form assets at higher levels.

In the typical plant or process, different people are involved in different functions. For example, functions associated with the process control activities, the device and equipment maintenance and monitoring activities, and the business activities such as process performance monitoring may each have a different interest in various levels of the process plant or among process plant. Process control operators generally oversee the day to day operation of the process and are primarily responsible for assuring the quality and continuity of the process operation typically affect the process by setting and changing set points within the process, tuning loops of the process, scheduling process operations such as batch operations, etc. As a result, process control operators may be primarily interested in the status of process loops, sub-unit, units and areas. Of course, this is not always the case, and process control operators may also be interested in the status of devices which may have an effect on the loops, sub-units, unit, areas, etc., for example.

On the other hand, maintenance personnel are primarily responsible for assuring that the actual equipment within the process is operating efficiently and for repairing and replacing malfunctioning equipment, use tools such as maintenance interfaces, as well and many other diagnostic tools which provide information about operating states of the devices within the process. As such, maintenance personnel may be primarily interested the status of devices and control loops, though maintenance personnel may further be interested in the status of sub-unit, units, etc.

Still further, other persons may be responsible for business applications, such as ordering parts, supplies, raw materials, etc., making strategic business decisions such as choosing which products to manufacture, what variables to optimize within the plant, etc. based on process performance measures. Likewise, managers or other persons may want to have access to certain information within the process plant or from other computer systems associated with the process plant for use in overseeing the plant operation and in making long term strategic decisions. Such persons may primarily be interested in status information pertaining to areas within a process plant, the process plant itself and even process plants that make up a business enterprise. As a result, a process plant may involve several persons interested in the status of devices, loops, sub-units, units, areas or the process plant at different hierarchical levels.

Because, for the most part, different personnel are interested in the status of different hierarchical levels within or among process plants, various systems within a process plant monitor and report the status of various devices that are connected to the process control systems of the plant, such as the relative health, performance, utilization, variability of the devices. For example, various systems may monitor the individual devices within a process plant. However, beyond the device level, the problem with this approach is that there are thousands of devices in a typical plant and the status of any single device generally cannot be used to determine the overall status of the loop, sub-unit, unit, area or process plant where the device is found.

Some solutions exist for determining the status of devices, loops, sub-units, units, area and/or plants. For example, it is currently known to provide an asset utilization expert that includes an index generation routine to generate indices related to the health, performance, utilization and variability of various plant assets at different levels of hierarchy. The creation of such indices is disclosed in Eryurek et al., U.S. Pat. No. 6,813,532 entitled “Creation and Display of Indices Within Process Plant” which was filed on Feb. 28, 2002 and issued on Nov. 2, 2004, and which is hereby expressly incorporated by reference herein. One manner in which an index could be generated by the index generation routine was to interconnect various models representing loops, sub-units, units, areas, etc. within the process plant to produce information regarding the operation of each loop, sub-unit, unit, area, etc. and generate an index from the data. Another manner in which an index was generated by the index generation routine was to create an index for each device and create an aggregate index at least level in the system hierarchy. The aggregate index could be a weighted average or a weighted combination of the indices of the assets that made up the larger asset.

However, within a typical process plant, some assets are considered more important than other assets within a group of assets. For example, some devices are considered more critical to the larger loop, sub-unit, unit, area, etc. of which the devices are a part. If such a device were to fail, it would have more of an impact on the loop, sub-unit, unit, area, etc. than if the other devices were to fail. Such a device would therefore deserve priority over the other devices. In turn, the remaining devices may have varying degrees of importance within the loop, sub-unit, unit or area. Likewise, some loops are more important than others among a group of loops interconnected to form a sub-unit, unit, area, etc. Similar situations exist among sub-units, units, area and even among plants. The importance of assets among a group of assets may greatly affect the overall status of the group. However, in the past, the varying degrees of importance among assets were not necessarily taken into account when determining the overall status of a group of assets.

SUMMARY

A system and method of monitoring an entity having a plurality of lower level entities, is described herein, which accounts for varying degrees of importance among the lower level entities. In one aspect, use indices pertaining to status information of the lower level entities is acquired. Further, weighting values are acquired. Generally, the weighing value pertains to the importance of a lower level entity among the plurality of lower level, such as the priority or criticality of the lower level entity. The weighing values may be based on the impact and frequency of failure of the lower level entity. The impact and/or frequency of failure may, in turn, be based on maintenance information, process data, diagnostic data, on-line monitoring data and/or heuristic data. An aggregate use index representing status information regarding the entity is creating from a combination of the lower level use indices and weighting values. The aggregate use index may be an aggregate health index indicating the health of the entity, an aggregate performance index indicating the relative performance of the entity, an aggregate variability index indicating an amount of deviation of a parameter of the entity or an aggregate utilization index indicating a degree of exploitation of the entity. The combination of the lower level use indices and weighting values may be a normalized expression, such that the range of values for the use indices is the same among the lower level entities. The combination may involve creating a weighted average of the use indices of the lower level entities.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a process plant having an asset utilization expert configured to receive and coordinate data transfer between many functional areas of the plant;

FIG. 2 is a data and information flow diagram with respect to the index aggregation routine within the plant of FIG. 1;

FIG. 3 is an exemplary depiction of a display representing a unit within a process control system that may be displayed by a graphical user interface;

FIG. 4 is an exemplary table that illustrates one manner in which indices may be generated for different levels of a system hierarchy;

FIG. 5 is an exemplary chart depicting one manner in which a performance index for a unit may be calculated;

FIG. 6 is an exemplary table that illustrates one manner in which index values may be used to calculate a new index value as a weighted average of the index values;

FIG. 7 is an exemplary table that illustrates one manner in which a variability index may be calculated for a unit;

FIG. 8 is an exemplary graphical display that may be provided by a graphical user interface;

FIG. 9 is an exemplary depiction of a display that may be provided by a graphical user interface to enable a user to view audit trail information; and

FIG. 10 is an exemplary graphical display that may be provided by a graphical user interface to enable a user to view an aggregate index;

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Referring now to FIG. 1, a process plant 10 includes a number of business and other computer systems interconnected with a number of control and maintenance systems by one or more communication networks. The process plant 10 includes one or more process control systems 12 and 14. The process control system 12 may be a traditional process control system such as a PROVOX or RS3 system or any other DCS which includes an operator interface 12A coupled to a controller 12B and to input/output (I/O) cards 12C which, in turn, are coupled to various field devices such as analog and Highway Addressable Remote Transmitter (HART) field devices 15. The process control system 14, which may be a distributed process control system, includes one or more operator interfaces 14A coupled to one or more distributed controllers 14B via a bus, such as an Ethernet bus. The controllers 14B may be, for example, DeltaVTM controllers sold by Fisher-Rosemount Systems, Inc. of Austin, Tex. or any other desired type of controllers. The controllers 14B are connected via I/O devices to one or more field devices 16, such as for example, HART or Fieldbus field devices or any other smart or non-smart field devices including, for example, those that use any of the PROFIBUS®, WORLDFIP®, Device-Net®, AS-Interface and CAN protocols. As is known, the field devices 16 may provide analog or digital information to the controllers 14B related to process variables as well as to other device information. The operator interfaces 14A may store and execute tools available to the process control operator for controlling the operation of the process including, for example, control optimizers, diagnostic experts, neural networks, tuners, etc.

Still further, maintenance systems, such as computers executing the AMS application or any other device monitoring and communication applications may be connected to the process control systems 12 and 14 or to the individual devices therein to perform maintenance and monitoring activities. For example, a maintenance computer 18 may be connected to the controller 12B and/or to the devices 15 via any desired communication lines or networks (including wireless or handheld device networks) to communicate with and, in some instances, reconfigure or perform other maintenance activities on the devices 15. Similarly, maintenance applications such as the AMS application may be installed in and executed by one or more of the user interfaces 14A associated with the distributed process control system 14 to perform maintenance and monitoring functions, including data collection related to the operating status of the devices 16.

The process plant 10 also includes various rotating equipment 20, such as turbines, motors, etc. which are connected to a maintenance computer 22 via some permanent or temporary communication link (such as a bus, a wireless communication system or hand held devices which are connected to the equipment 20 to take readings and are then removed). The maintenance computer 22 may store and execute known monitoring and diagnostic applications 23, for example RBMware™ sold by CSI Systems of Knoxville, Tenn. or other any other known applications used to diagnose, monitor and optimize the operating state of the rotating equipment 20. Maintenance personnel usually use the applications 23 to maintain and oversee the performance of rotating equipment 20 in the plant 10, to determine problems with the rotating equipment 20 and to determine when and if the rotating equipment 20 must be repaired or replaced.

Similarly, a power generation and distribution system 24 having power generating and distribution equipment 25 associated with the plant 10 is connected via, for example, a bus, to another computer 26 which runs and oversees the operation of the power generating and distribution equipment 25 within the plant 10. The computer 26 may execute known power control and diagnostics applications 27 such as those provided by, for example, Liebert and ASCO or other companies to control and maintain the power generation and distribution equipment 25.

A computer system 30 is provided which is communicatively connected to the computers or interfaces associated with the various functional systems within the plant 10, including the process control functions 12 and 14, the maintenance functions such as those implemented in the computers 18, 14A, 22 and 26 and the business functions. In particular, the computer system 30 is communicatively connected to the traditional process control system 12 and to the maintenance interface 18 associated with that control system, is connected to the process control and/or maintenance interfaces 14A of the distributed process control system 14, is connected to the rotating equipment maintenance computer 22 and to the power generation and distribution computer 26, all via a bus 32. The bus 32 may use any desired or appropriate local area network (LAN) or wide area network (WAN) protocol to provide communications.

As illustrated in FIG. 1, the computer 30 is also connected via the same or a different network bus 32 to business system computers and maintenance planning computers 35 and 36, which may execute, for example, enterprise resource planning (ERP), material resource planning (MRP), computer maintenance management systems (CMMS), accounting, production and customer ordering systems, maintenance planning systems or any other desired business applications such as parts, supplies and raw materials ordering applications, production scheduling applications, etc. The computer 30 may also be connected via, for example, the bus 32, to a plantwide LAN 37, a corporate WAN 38 as well as to a computer system 40 that enables remote monitoring of or communication with the plant 10 from remote locations.

In one embodiment, the communications over the bus 32 occur using the XML/XSL protocol. Here, data from each of the computers 12A, 18, 14A, 22, 26, 35, 36, etc. is wrapped in an XML/XSL wrapper and is sent to an XML/XSL data server which may be located in, for example, the computer 30. Because XML/XSL is a descriptive language, the server can process any type of data. At the server, if necessary, the data is encapsulated with a new XML/XSL wrapper, i.e., this data is mapped from one XML/XSL schema to one or more other XML/XSL schemas which are created for each of the receiving applications. Thus, each data originator can wrap its data using a schema understood or convenient for that device or application, and each receiving application can receive the data in a different schema used for or understood by the receiving application. The server is configured to map one schema to another schema depending on the source and destination(s) of the data. If desired, the server may also perform certain data processing functions or other functions based on the receipt of data. The mapping and processing function rules are set up and stored in the server prior to operation of the system described herein. In this manner, data may be sent from any one application to one or more other applications.

Generally speaking, the computer 30 stores and executes an asset utilization expert 50 that collects data and other information generated by the process control systems 12 and 14, the maintenance systems 18, 22 and 26 and the business systems 35 and 36 as well as information generated by data analysis tools executed in each of these systems. The asset utilization expert 50 may be based on, for example, the OZ expert system currently provided by NEXUS. However, the asset utilization expert 50 may be any other desired type of expert system including, for example, any type of data mining system. Importantly, the asset utilization expert 50 operates as a data and information clearinghouse in the process plant 10 and is able to coordinate the distribution of data or information from one functional area, such as the maintenance area, to other functional areas, such as the process control or the business functional areas. The asset utilization expert 50 may also use the collected data to generate new information or data which can be distributed to one or more of the computer systems associated with the different functions within the plant 10. Still further, the asset utilization expert 50 may execute or oversee the execution of other applications that use the collected data to generate new types of data to be used within the process plant 10.

In particular, the asset utilization expert 50 may include or execute index generation software 51 that creates indices associated with devices, like process control and instrumentation devices, power generation devices, rotating equipment, units, areas, etc, or that are associated with process control entities, like loops, etc. within the plant 10. The asset utilization expert 50 may further include or execute an index aggregation routine 60. The index aggregation routine 60 utilizes indices generated by the index generation routine 51 or other index generation routines to create indices associated with various levels within a process control system, or more generally an asset utilization system, which may include one or more process control systems. The index aggregation routine 60 further includes a weighting value when creating an aggregate index associated with a process, unit, area, The index aggregation routine 60 may be provided as a separate routine or as part of the index generation routine 50.

The indices generated by the index generation routine 51 and/or the index aggregation routine 60 can then be provided to the process control applications to help optimize process control and can be provided to the business software or business applications to provide the business persons more complete or understandable information associated with the operation of the plant 10. The asset utilization expert 50 can also provide maintenance data (such as device status information) and business data (such as data associated with scheduled orders, timeframes, etc.) to a control expert 52 associated with, for example, the process control system 14 to help an operator perform control activities such as optimizing control. The control expert 52 may be located in, for example, the user interface 14A or any other computer associated with the control system 14 or within the computer 30 if desired. In one embodiment, the control expert 52 may be, for example, the control expert described in U.S. patent application Ser. Nos. 09/256,585 and 09/499,445 identified above.

Additionally, the asset utilization expert 50 can send information to one or more optimizers 55 within the plant 10. For example, a control optimizer 55 can be located in the computer 14A and can run one or more control optimization routines 55A, 55B, etc. Additionally or alternatively, optimizer routines 55 could be stored in and executed by the computer 30 or any other computer, and the data necessary therefore could be sent by the asset utilization expert 50. If desired, the plant 10 may also include models 56 that model certain aspects of the plant 10 and these models 56 can be executed by the asset utilization expert 50 or a control or other expert such as the control expert 52 to perform modeling functions, the purpose of which is described in greater detail in U.S. patent application Ser. No. 10/085,439 entitled “Creation and Display of Indices in a Process Plant,” which was filed on Feb. 28, 2002, which is expressly incorporated by reference herein. Generally speaking, however, the models 56 can be used to determine device, area, unit, loop, etc. parameters, to detect faulty sensors or other faulty equipment, as part of optimizer routines 55, to generate indices such as performance and utilization indices for use in the plant 10, to perform performance or condition monitoring, as well as for many other uses. The models 56 may be models such as those created by and sold by MDC Technology located in Teeside, England or may be any other desired types of models. Some of the data generated by the models 56 may be used by the index generation routine 51 to generate indices which are used in other applications, such as business and process control applications.

The asset utilization expert 50 receives data as it is generated or at certain periodic times over, for example, the bus 32 or other any communication network within the process plant 10. Thereafter, periodically or as needed, the asset utilization expert 50 redistributes the data to other applications or uses that data to generate and provide other information useful in different aspects of the control or operation of the process plant 10 to other function systems within the plant 10. In particular, the asset utilization expert 50 may supply data to cause the index generation routine 51 to create a series of composite indices such as a performance index, a utilization index, a health index and a variability index associated with one or more of the devices, units, loops, areas, or other entities within the process plant 10. The generation and use of these indices will also be discussed in more detail herein.

As a result of the above discussion, it can be seen that the use of models provides many new types of data or information for the business applications, process control applications and asset maintenance and monitoring applications. In particular, the models can be used to perform performance monitoring and to produce a performance index which indicates the relative performance of a device, unit, area, etc. within a plant. This performance index may be a measure of the performance of an entity with respect to the possible performance of that entity. Furthermore, while device and unit models have been discussed above, similar models could be made and executed for process control entities, such as loops, units, etc. to provide performance measures and optimization criteria for these types of entities as well. Also, as indicated above, models may, in some cases, be used to measure or indicate the health of certain devices or other entities and to provide a health index indicative of these entities. For example, the error measurements of certain input and output sensors as determined by the regression analysis used on certain models may be used as or converted into an indication of the health of those devices. Also, other information not otherwise available to the process controller, such as model parameters and virtual sensor measurements based on the models could be provided to the process controllers or to the business persons for use in numerous manners.

Besides performance and health indices, the asset utilization expert 50 can assist the index generation routine 51 in creating other types of indices such as a utilization index and a variability index. A variability index indicates how much some signal into or out of, or some other parameter associated with a device, loop, unit, etc. varies as compared to how much this signal or parameter is expected to vary. The data needed to create this variability index may be collected by the asset utilization expert 50 and provided to the index generation routine 51 at any desired or convenient times. Of course, the normal amount of variation of a signal or parameter may be set by a manufacturer, engineer, operator or maintenance person familiar with the entity or may be based on a statistical measure (such as an average, standard deviation, etc.) associated with that or other similar entities within the plant and this normal or expected variation may be stored by or updated within the index generation routine 51 or the index aggregation routine 60.

The utilization index, in one form or another, tracks or reflects the utilization of individual devices, units, loops, or other entities and may provide some indication as to whether these entities are being over utilized or under utilized based on previously determined bench marks or operational goals. A utilization index can be generated based on measured uses of the actual device. For example, a device may be measured as to how often it is being used within a process or is being left idle and this index may be compared to a desired utilization for that entity to determine if the entity is being over or under utilized. The utilization index might identify devices, units, loops, etc. which are not being utilized as often as they could be or should be or, on the other hand, which are being utilized too much and, thus, are being over used. In some instances, a utilization index might be determined based on the business decisions made regarding the appropriate or desired use of a particular device.

Referring now to FIG. 2, a data flow diagram illustrating some of the data flow between an index aggregation routine 60 and other data tools or data sources within the process plant 10 is provided. In one embodiment, an index aggregation routine 60 receives information from information sources which may run various routines and applications for providing status information regarding devices, loops, units, areas, etc. within a process plant. The index aggregation routine 60 may be incorporated with a central data collecting, sharing and distribution application, such as the asset utilization expert 50 described above which receives much of the status information from the various data tools and data sources, or provided as a separate application. The index aggregation routine 60 may be centrally located at a particular server, which may be maintained locally at the plant 10 or remotely from the plant 10. Alternatively, the index aggregation routine 60 may be distributed among several computers such as business system computers 35, maintenance computers 18, 22, maintenance planning computers 36. Furthermore, the index aggregation routine 60 may be a network application available over the Internet and/or the plantwide LAN 37 and available to various personnel through user interfaces 12A, 14A, 58.

As mentioned above, the index aggregation routine 60 receives information from various data sources, which may include data collectors, data generators or data tools including index generation routines 51, model generation routines 56, control routines 62, maintenance system applications 64, data historians 66, diagnostic routines 68, etc. In one embodiment, the index aggregation routine 60 may receive information from the asset utilization expert 50 described above, and which is described further in U.S. patent application Ser. No. 10/085,439 referred to above. This information may include indices related to the health, performance, utilization and variability of a particular device, loop, unit, area, etc. This data can take on any desired form based on how the data is generated or used by other functional systems. Still further, this data may be sent to the index aggregation routine 60 using any desired or appropriate data communication protocol and communication hardware, such as the XML/XSL protocol discussed above.

Information received from the index generation routines 51, model generation routines 56, control routines 62, maintenance system applications 64, data historians 66, diagnostic routines 68, etc. may be used to create and assign a weighting value to each of the devices within a logical and/or physical group of device. For example, each device within a logical process (e.g., control loop), sub-unit, unit, area or plant may be assigned a weighting value. Further, weighting values may be created and assigned to logical and/or physical groups including a logical process, a sub-unit, an area or a plant.

The weighting value generally relate to the importance or priority of a device, loop, sub-unit, etc. among the corresponding devices, loops, sub-units, etc. within the same physical and/or logical grouping. In other words, each asset within a group is ranked according to system criticality, operational criticality, asset criticality, etc. based upon an assessment of each asset within the group, and a weighing value is assigned to each asset based upon its importance. For example, within a sub-unit that includes a plurality of devices and/or loops, a particular piece of rotating equipment 20 may be considered more critical to the operation of the overall sub-unit than a field device 16. If both the rotating equipment 20 and the field device 16 require maintenance, the rotating equipment 20 may receive priority over the field device 16 in terms of resources allocated to maintenance. As a result, the rotating equipment 20 is assigned a weighting value greater than the weighting value assigned to the field device 16. Similarly, among the sub-units and/or units within an area, a particular sub-unit may be considered more important to the area than another sub-unit, and is weighted accordingly. It should be recognized that areas within a plant may be weighted according to importance, and plants within a business enterprise may likewise be weighted. It should further be recognized that assets within a grouping need not be limited to an immediately preceding level. For example, weighting values may be assigned to each device, loop, sub-unit and/or unit within an area, rather than just each unit within an area. Likewise, weighting values may be assigned to each device, loop, sub-unit, unit and/or area in a plant. A user may define the groupings in a manner most helpful to the user, and weighting values may be assigned accordingly. As a result, each device, loop, sub-unit, unit, area, plant, etc. may be weighted according to its importance within a particular grouping, such that each asset within a given group is assigned a weighting value.

Generally, the importance of a device, loop, sub-unit, unit, area, etc., and its corresponding weighting value, is based on two contributing factors: the impact on the group when the asset fails and the frequency of failure. For example, a device that has little impact on an area when it fails may be weighted lower than a device that has a high impact on an area during failure. Likewise, a device that has a low frequency of failure may be weighted lower than a device with a high frequency of failure. The impact and the frequency of failure may be quantified, with the product of the impact and frequency of failure resulting in the weighting value. The evaluation of impact and frequency of failure may be based on a variety of factors, including, but not limited to, process information, on-line monitoring information, historical information, maintenance information, diagnostic information, and heuristic information based on experience of process plant personnel.

The index aggregation routine 60 may acquire weighting values related to each device, loop, sub-unit, unit, area, plant, etc. within a group by receiving each weighting value from another source or by creating each weighting value based on information from a variety of sources. For example, the index aggregation routine 60 may receive data relating to the impact and frequency of failure of each device, loop, sub-unit, unit, area, plant, etc. within a group and create each weighting value based on the impact and frequency of failure, (e.g., the product of the impact and frequency of failure).

In yet another example, the index aggregation routine 60 may receive information relating to each device, loop, sub-unit, unit, area, plant, etc within a group to evaluate the impact and frequency of failure of each asset within the group, and to further create a weighting value for each asset within the group. The information may include process information, on-line monitoring information, historical information, maintenance information, diagnostic information, and heuristic information as described above. Accordingly, the index aggregation routine 60 is communicatively coupled to model generation routines 56, control routines 62, maintenance system applications 64, data historians 66, diagnostic routines 68, or other data sources as shown in FIG. 2. Each of the various types of information may be used to evaluate the impact and/or frequency of failure of an asset within a group of assets. For example, historical information, diagnostic information and maintenance information may provide information regarding previous failures of a device, while historical information, process information, on-line monitoring information and heuristic information may provide information on the impact of past failures on the group or the predicted impact of a failure on the group. Of course, it should be recognized that the weighting values may be created in a similar manner using other routines or systems within the process plant, including the asset utilization expert 50 or the index generation routine 51, or created outside the process plant.

In addition to acquiring weighting values pertaining to each device, loop, sub-unit, unit, area, plant, etc within a group, the index aggregation routine 60 acquires indices pertaining to the status of each device, loop, sub-unit, unit, area, plant, etc within the group. The indices may be acquired from the index generation routine 51, and each index may include a health index, a utilization index, a performance index or a variability index as described above. Examples of each index and its creation are described further below and described further in U.S. patent application Ser. No. 10/085,439 referred to above. However, it should be understood that various other indices may be used by the index aggregation routine 60 to determine an aggregate index for a group.

Accordingly, weighting values may be acquired by receiving the weighting values, by receiving impact and frequency of failure information to create the weighting values or by receiving information from the model generation routines 56, control routines 62, maintenance system applications 64, data historians 66, diagnostic routines 68, etc. to evaluate the impact and frequency of failure and create a weighting value for each of the devices, loops, sub-unit, units, areas and/or plants, etc. within a logical and/or physical group. Further, indices pertaining to each devices, loops, sub-unit, units, areas and/or plants, etc. within the logical and/or physical group may be acquired by the index aggregation routine 60. Using the weighting values and indices, the index aggregation routine 60 may create an aggregate index pertaining to the overall status of the group, such as an aggregate health index, an aggregate utilization index, an aggregate performance index or an aggregate variability index. The index aggregation routine 60 may calculate the aggregate index as a weighted average according to the following general equation:

u = i = 1 n w i u i i = 1 n w i ( 1 )
wherein:

    • u=the aggregate index of the group
    • n=the number of assets within the group
    • hi=the index for the ith asset
    • wi=the weight of the ith asset

As seen by the above equation, the aggregate index for a group is created as a normalized expression in which the range of the aggregate index is within the range of the indices used to create the aggregate index. This allows the above expression to be used with various index ranges, and allows the aggregate index to be used with various asset groups having assets of differing importance. In particular, the index value for each asset within the group is within a common range of index values and the weighting value for each asset within the group within a common range of weighting values. As a result, the aggregate index for the group will be within the same range and the range used for the indices of the assets within the group. For example, the value for ui may be a number from 0 to 100, where “0” corresponds to known use index that is low (e.g., poor health, poor performance, low utilization, high variability, etc.) and “100” corresponds to a high index (e.g., excellent health, excellent performance, high utilization, low variability, etc.). Accordingly, the aggregate index u is provided as a number from 0 to 100, which corresponds to the range of indices used by the assets within the group. Further, wi may be a number from 0 to 100, where “0” corresponds to a known, yet low, importance and “100” corresponds to a high importance.

Although the above example shows ui and wi having the same range of values, the range of values for the indices may be different from the range used for the weighting values. In some instances, an index and/or a weighting value may not be known or otherwise available for a particular asset within the group, in which case it is difficult to make assumptions about a particular asset's index and/or importance. As such, the value for ui and/or wi is set to null to avoid skewing the resulting aggregate index. In a scenario where all weighting values are zero, the aggregate index defaults to zero to avoid division by zero. The above ranges are provided as examples only, and different ranges may be used consistent with the above parameters.

In operation, the index aggregation routine 60 acquires indices pertaining to the status of each asset within a group and acquires weighting values pertaining to the importance (e.g., criticality, priority) of each asset within a particular group to create an aggregate index pertaining to the overall group. For example, an area may include several devices, loops, sub-units and units. By acquiring the health index values and weighting values for each device within the area, the overall health of the area may be determined. Alternatively, the aggregate health index of the area may be calculated based on the loops, sub-units or units within the area, or based on a combination of devices, loops, sub-units and units within the area. In turn, the index aggregation routine 60 may calculate the health index of each area within a plant, or receive the area health indices from the index generation routine 51, acquire a weighting value for each area within the plant and generate an aggregate health index corresponding to the overall health of the plant. Similar aggregate indices may be determined for loops, sub-units, units, business enterprises or at any other level of hierarchy.

In general, each of the indices generated by the index generator routine 51 may be calculated for individual devices, for logical and/or physical groupings of devices, for logical processes (e.g., control loops), for logical groupings of devices such as units and areas, plant, etc. On the other hand, each of the indices generated by the index aggregation routine 60 may be calculated based on indices provided by the index generation routine 51, based on indices previously determined by the index aggregation routine 60, or other sources of indices, and further based on weighting values associated with each of the devices, logical and/or physical groupings of devices, logical processes, units, areas, plant, etc. to calculate aggregate indices for logical and/or physical groupings of devices, for logical processes (e.g., control loops), for logical groupings of devices such as units and areas, plant, etc. In other words, the indices may, in principal, be calculated at each level of the equipment and logical hierarchy of a process control system or, more generally, an asset utilization system, which may include one or more process control systems. However, the meaning of a particular index may depend on the context (i.e., whether the index corresponds to a logical or a physical grouping of devices and/or parameters) in which the index is generated and displayed and may depend on the level of the hierarchy at which it is displayed. For example, at the lowest level of the equipment hierarchy, indices correspond to physical devices such as valves, temperature sensors, actuators, etc. Thus, each device may have a unique set of indices that may be generated within the device or for the device based on information stored within the device at the time the device is manufactured. Accordingly, each device may generate and provide its indices to higher levels of the hierarchy and to the asset utilization expert 50 as needed.

Similarly, units or loops, each of which is composed of one or more devices or function blocks may each have a unique set of indices. However, the index values for each unit or loop may be generated by mathematically combining the index values for the individual devices or function blocks used within the unit or loop. Thus, if a unit or loop is composed of a pressure transmitter, a valve and a pump (or function blocks associated with the operation of these devices), the index values for the unit or loop may be based on various mathematical combinations of the index values generated for or by each of those devices or function blocks making up the unit or the loop. Likewise, because sub-unit and unit levels of the hierarchy are composed of one or more loops which, in turn, are composed of devices, the index values for each sub-unit and unit may be generated by mathematically combining loop or device index values. Still further, area indices may be determined as combinations of the units, loops, devices, etc. within the area.

Also, generally speaking, the one or more user interface routines 58 can be stored in and executed by one or more of the computers within the plant 10. For example, the computer 30, the user interface 14A, the business system computer 35 or any other computer may run a user interface routine 58. Each user interface routine 58 can receive or subscribe to information from the asset optimization expert 50, including the index generation routine 51 and either the same or different sets of data may be sent to each of the user interface routines 58. Any one of the user interface routines 58 can provide different types of information using different screens to different users. For example, one of the user interface routines 58 may provide a screen or set of screens to a control operator or to a business person to enable that person to set constraints or to choose optimization variables for use in a standard control routine or in a control optimizer routine. The user interface routine 58 may provide a control guidance tool that enables a user to view the indices created by the index generation software 51 in some coordinated manner. This operator guidance tool may also enable the operator or any other person to obtain information about the states of devices, control loops, units, etc. and to easily see the information related to the problems with these entities, as that information has been detected by other software within the process plant 10. The user interface routine 58 may also provide performance monitoring screens using performance monitoring data provided by or generated by the tools 23 and 27, the maintenance programs such as the AMS application or any other maintenance programs. Of course, the user interface routine 58 may provide any user access to and enable the user to change preferences or other variables used in many or all functional areas of the plant 10.

One important aspect of the system of FIG. 1 is the user interface routines 58 which provide a graphical user interface (GUI) that is integrated with the asset utilization expert 50 described herein to facilitate a user's interaction with the various asset utilization capabilities provided by the asset utilization expert 50. However, before discussing the GUI in greater detail, it should be recognized that the GUI may include one or more software routines that are implemented using any suitable programming languages and techniques. Further, the software routines making up the GUI may be stored and processed within a single processing station or unit, such as, for example, a workstation, a controller, etc. within the plant 10 or, alternatively, the software routines of the GUI may be stored and executed in a distributed manner using a plurality of processing units that are communicatively coupled to each other within the asset utilization system.

Preferably, but not necessarily, the GUI may be implemented using a familiar graphical windows-based structure and appearance, in which a plurality of interlinked graphical views or pages include one or more pull-down menus that enable a user to navigate through the pages in a desired manner to view and/or retrieve a particular type of information. The features and/or capabilities of the asset utilization expert 50 described above may be represented, accessed, invoked, etc. through one or more corresponding pages, views or displays of the GUI. Furthermore, the various displays making up the GUI may be interlinked in a logical manner to facilitate a user's quick and intuitive navigation through the displays to retrieve a particular type of information or to access and/or invoke a particular capability of the asset utilization expert 50.

Generally speaking, the GUI described herein provides intuitive graphical depictions or displays of process control areas, units, loops, devices, etc. Each of these graphical displays may include numerical status and indices (some or all of which may be generated by the index generator routine 51 and the index aggregation routine 60 described above) that are associated with a particular view being displayed by the GUI. For example, a display depicting a process control area may provide a set of indices reflecting the status and performance of that area (i.e., a particular portion of the process control system at a particular level of the equipment hierarchy). On the other hand, a display depicting a loop may provide a set of status and performance indices associated with that particular loop. In any event, a user may use the indices shown within any view, page or display to quickly assess whether a problem exists within any of the devices, loops, etc. depicted within that display.

Additionally, the GUI described herein may automatically, or may in response to a request by a user, provide maintenance information to the user. The maintenance information may be provided by any portion of the asset utilization expert 50. Similarly, the GUI may display alarm information, process control information, etc., which may also be provided by the asset utilization expert 50. Still further, the GUI may provide messages to the user in connection with a problem that has occurred or which may be about to occur within the plant 10. These messages may include graphical and/or textual information that describes the problem, suggests possible changes to the system which may be implemented to alleviate a current problem or which may be implemented to avoid a potential problem, describes courses of action that may be pursued to correct or to avoid a problem, etc.

Generally speaking, the GUI described herein provides intuitive graphical depictions or displays of process control areas, units, loops, devices, etc. Each of these graphical displays may include numerical status and performance indices (some or all of which may be generated by the index generator routine 51 described above) that are associated with a particular view being displayed by the GUI. For example, a display depicting a process control area may provide a set of indices reflecting the status and performance of that area (i.e., a particular portion of the process control system at a particular level of the equipment hierarchy). On the other hand, a display depicting a loop may provide a set of status and performance indices associated with that particular loop. In any event, a user may use the indices shown within-any view, page or display to quickly assess whether a problem exists within any of the devices, loops, etc. depicted within that display.

Additionally, the GUI described herein may automatically, or may in response to a request by a user, provide maintenance information to the user. The maintenance information may be provided by any portion of the asset utilization expert 50. Similarly, the GUI may display alarm information, process control information, etc., which may also be provided by the asset utilization expert 50. Still further, the GUI may provide messages to the user in connection with a problem that has occurred or which may be about to occur within the plant 10. These messages may include graphical and/or textual information that describes the problem, suggests possible changes to the system which may be implemented to alleviate a current problem or which may be implemented to avoid a potential problem, describes courses of action that may be pursued to correct or to avoid a problem, etc.

FIG. 3 is an exemplary depiction of a display representing a unit 100 within a process control system that may be displayed by the GUI. As illustrated in FIG. 3, the unit 100 includes a plurality of devices such as, for example, valves, pumps, temperature transmitters, etc., all of which may be depicted graphically as shown. Additionally, the display may further include lines arrows, and any other indicia to represent logical and physical interconnections between the various devices. Of course, such graphical representations of process control systems (or portions of process control systems) are well known in the art and, thus, the manner of implementing these graphical representations or displays will not be described in further detail herein.

Importantly, the GUI display shown in FIG. 3 also includes a plurality of index names and values 150. In particular, the index names and values 150 include a performance index, a health index, a variability index and a utilization index, all of which have been discussed briefly above in connection with the asset utilization expert 50, the index generation routine 51 and the index aggregation routine 60. The index names and values 150 may be displayed in a tabular format as shown or in any other desired format. The index names and values 150 are representative of the performance and status of the entire unit 100 and, thus, the index values shown are preferably, but not necessarily, composed of the index values associated with each of the sub-units and/or devices that make up the unit 100.

Indices generated by the index generation routine 51 and the index aggregation routine 60, including, but not limited to a performance index, a health index, a variability index and a utilization index, may be displayed by the GUI as described in detail herein in connection with the various displays of the GUI, additional and/or different indices may be generated by the asset utilization expert 50 and displayed via the GUI without departing from the scope of the invention.

As discussed in greater detail above, the mathematical combination of device index values to form index values for loop, sub-unit, unit and area levels of the hierarchy may use weighted summations or averages, or any other suitable mathematical combination. Of course, the calculation of one or more of the performance, health, variability and utilization indices may not be appropriate, required or useful for every level of the logical and equipment hierarchies. FIG. 4 is an exemplary table that illustrates one manner in which the performance index (PI), the health index (HI), the variability index (VI) and the utilization index (UI) may or may not be generated for the device, loop, sub unit and unit levels of the system hierarchy. As shown in FIG. 4, the PI may be generated for the unit and sub unit levels. At the unit and sub unit levels, the PI may be calculated by comparing a model (such as one of the models 56) of the unit or sub unit to the actual performance of the unit or sub unit or in any other desired manner. In particular, the PI in this context (i.e., at the unit and sub unit levels of the hierarchy) may be, for example, an efficiency with respect to a theoretical maximum or, alternatively, with respect to an empirically derived maximum efficiency based on actual system performance. The table shown in FIG. 4 also indicates that the PI need not be calculated for individual devices or loops. However, in some applications it may be desirable to calculate a PI for loops and devices. For example, in the case of calculating a PI for a device, the device manufacturer may store performance information within the device so that during operation the device may calculate a PI based on a comparison of an actual performance characteristic (such as, for example, an operating efficiency) to stored performance information, which may include a theoretical maximum device efficiency. Of course, the index generation routine 51 or index aggregation routine 60 may also perform this function. In the case of calculating a PI for a loop, the system may, for example, compare the maximum or average loop error (i.e., the steady state error signal) to some predetermined minimum error value which, ideally, may be zero. In this manner, a small loop error may correspond to a PI value that is indicative of good performance.

FIG. 4 also illustrates that the VI may be calculated at the loop and device levels of the hierarchy. At the device level, the VI may be calculated by comparing the changes or deviations in a device output to an expected or desired amount of change or variation. An excessively high or an excessively low VI value may be indicative of a device failure or malfunction or possibly an imminent failure or malfunction. Likewise, at the loop level, excessively frequent or large magnitude changes in the output of a loop may be indicative of a problem. In any case, the VI for loops and devices may be based on a comparison of actual parameter variability to expected parameter variability, which may be determined theoretically or empirically. Although FIG. 4 shows that the VI may not be calculated for the unit and sub unit levels, in some applications, it may nevertheless be desirable to generate a VI for these levels.

Further, FIG. 4 shows that the HI is calculated for the device, loop, sub unit and unit levels. The HI for a device may be based on historical usage of the device. In particular, the device manufacturer may store information relating to the life cycle of the device within the device and, based on the usage of the device and the environmental impacts imparted to the device during its operation (e.g., temperature variations, shocks, etc.), the device may determine to what extent the device has moved along its life cycle curve (i.e., aged). The manufacturer may program a device to provide an HI value which is indicative of the current status of the life cycle of the device. For example, a stroke type valve may have an expected useful operating life cycle of 250,000 full stroke cycles and the manufacturer of the stroke valve device, which is typically a smart field device, has stored in its memory the expected number of lifetime operating strokes along with the current number strokes that the valve has completed. Thus, in the case where an HI value may range from between zero and ten (where zero represents poor health and ten represents perfect health), the HI value generated by the valve may range from zero to ten as the number of strokes rises from zero to 250,000. Of course, the precise relationship between the HI values and the life cycle characteristic (e.g., strokes) may not be linear. To the contrary, many life cycle characteristics follow an exponential or polynomial characteristic, whereby failure and degradation in device performance/operation progresses more rapidly as time passes, as strokes are completed, etc. Of course, there are many other manners of defining or computing an HI for a device, based on the current detected state of the device and how well it is operating. For example, if the device has two detected minor problems, its HI may decrease.

The HI for a loop, on the other hand, is preferably, but not necessarily, a mathematical combination (such as, for example, a weighted summation or average) of the HI values for the individual devices or functions blocks that make up the loop. Likewise, the HI values for the sub unit and unit levels may also be a mathematical combination of the underlying HI values for loops and sub units. Thus, ultimately, the HI values hierarchy for levels above the device level are based on one or more HI values for devices that have been formed into composite values.

As is also shown in FIG. 4, the UI may be calculated for the loop, sub unit and unit levels, but may not necessarily be calculated for the device level. Generally speaking, the UI represents the degree to which a particular asset (e.g., a loop, a sub unit or a unit) is being exploited in comparison to its capacity or desired utilization. For example, the UI value may be based on the amount of time for which a unit, sub unit or loop is being used to perform control or produce outputs. Additionally or alternatively, the UI value may be based on the amount of material which is being processed by the loop, sub unit and/or unit in comparison to the maximum amount that may be processed by that loop, sub unit, unit, etc.

FIG. 5 is an exemplary chart depicting one manner in which the PI for the unit 100 shown in FIG. 3 may be calculated. As shown in FIG. 5, each of a plurality of loops 175 that make up the unit 100 has its own PI and weighting coefficient, which may be user selected or defined based on the relative importance of that particular loop to the overall operation of the unit 100. The indices and weights for the loops 175 may then be mathematically combined using the index aggregation routine 60 to arrive at a PI value of 81.8 for unit 100.

In a similar manner, the HI for the unit 100 may be calculated as a weighted average of the HI values for all of the devices (and/or loops) that make up the unit 100. A table such as that shown in FIG. 6 may be used to represent the values to be included in the weighted average. As is also shown in FIG. 6, a textual description may be associated with particular devices and index values. These textual descriptions may provide diagnostic information, maintenance information, etc. based on the HI value and the particular device associated with that HI value.

FIG. 7 is an exemplary table that illustrates one manner in which the VI may be calculated for a unit, such as the unit 500 shown in FIG. 3. As with the HI, the VI calculated for the unit 500 of FIG. 3 is based on a weighted average of the VI values for the individual devices, loops and/or sub units that make up the unit 500. Of course, the GUI may provide a user with the ability to see the weighted average data such as that illustrated in FIGS. 10-12 and may enable the user to change the weights.

FIG. 8 is an exemplary graphical display that may be provided by the GUI to enable a user to quickly analyze the operational status and performance of a process area within the plant 10. As shown in FIG. 8, the GUI may graphically depict the physical equipment (and the interconnections therebetween) within a process area 200. Of course, it should be recognized that although a process area is depicted within the GUI display shown in FIG. 8, any other portion of the plant 10 such as, for example, a unit, sub unit, loop, device, etc. may be shown instead to achieve the same or similar results. In any event, the process area 200 is depicted as having a pair of tanks, a plurality of temperature transmitters, pressure transmitters, flow transmitters, etc. and pipes, all of which may be interconnected as shown in FIG. 8. Further, each of the physical devices may be displayed along with an associated alphanumeric identifier (e.g., TT-394) that uniquely identifies that device within the plant 10 and may also be displayed along with a graphic meter or gauge (i.e., the partially shaded semi-circular features) that enables a user to quickly determine the status of the sensing parameter associated with that device. For example, the GUI may display a graphic meter or gauge associated with a temperature transmitter and may shade more or less of the meter based on the temperature currently being sensed by the temperature transmitter. Importantly, one or more of the VI, HI, UI and PI values may be displayed for one or more of the devices shown within the area 200. By way of example only, the HI values for several of the devices that are connected to a tank 210 within the area 200 are displayed. However, more or fewer HI values could be displayed if desired. Additionally, different index values or groups of index values may be displayed for any of the devices that appear within the area 200 as desired. As can be appreciated from the display shown in FIG. 8, a user can quickly ascertain whether an area is performing properly and will continue to perform properly. Further, a user can also quickly identify those devices, units, sub units, etc. that may need attention and/or which may be causing a particular problem.

It will also be understood that a user may view successively lower and lower entities within a plant and be provided information about the indices associated with each of these different entities or views. Thus, for example, a user may look at a view of the plant and see a particular set of indices for the plant. The user may then focus on one area, such as by clicking on one of the areas within the plant view, and see the indices associated with that area. Similarly, by clicking on units within the displayed area, the indices for different units may be viewed. Likewise indices for loops, sub units, devices etc. may then be viewed by focusing in on these different entities from a view of an entity in which these entities are located. In this manner, a user can quickly find the cause of a lower than (or higher than) expected index at any point or level of the plant.

FIG. 9 is an exemplary depiction of a display that may be provided by the GUI to enable a user to view audit trail information in connection with any device used within the area 200. By way of example, a user may use a mouse to click on a given device or its alphanumeric identifier or, alternatively, may enter the identifier via a keyboard, to request a pop-up audit trail window 250 for that device. In this manner, a user can use the audit trail information to determine whether an improper or unacceptable index value may be related to a failure to calibrate the device properly or in a timely manner, whether a device has been configured properly or at all, etc.

FIG. 10 is exemplary depiction of a display that may be provided by the GUI to enable a user to view an aggregate index in connection with an area. By way of example, an aggregate health index of the area, as determined by the index aggregation routine 60, is provided at the top left of the display, with the devices of the area displayed below. A user may use a mouse to click on a given device or its alphanumeric identifier or, alternatively, may enter the identifier via a keyboard, to request a window for that device. In this manner, a user can view additional detailed information about the device, such as its weighting value, its health index, description, location, alerts, etc. to determine whether an improper or unacceptable index value associated with the area may be related to a failed device within the area.

While the asset utilization expert 50, index generation routine 51, index aggregation routine 60 and other process elements have been described as preferably being implemented in software, they may be implemented in hardware, firmware, etc., and may be implemented by any other processor associated with the process control system 10. Thus, the elements described herein may be implemented in a standard multi-purpose CPU or on specifically designed hardware or firmware such as an application-specific integrated circuit (ASIC) or other hard-wired device as desired. When implemented in software, the software routine may be stored in any computer readable memory such as on a magnetic disk, a laser disk, or other storage medium, in a RAM or ROM of a computer or processor, in any database, etc. Likewise, this software may be delivered to a user or a process plant via any known or desired delivery method including, for example, on a computer readable disk or other transportable computer storage mechanism or over a communication channel such as a telephone line, the internet, wireless communication, etc. (which are viewed as being the same as or interchangeable with providing such software via a transportable storage medium).

Thus, while the present invention has been described with reference to specific examples, which are intended to be illustrative only and not to be limiting of the invention, it will be apparent to those of ordinary skill in the art that changes, additions or deletions may be made to the disclosed embodiments without departing from the spirit and scope of the invention.

Patent Citations
Cited PatentFiling datePublication dateApplicantTitle
US3096434Nov 28, 1961Jul 2, 1963Daniel Orifice Fitting CompanyMultiple integration flow computer
US3404264Jul 19, 1965Oct 1, 1968American Meter CoTelemetering system for determining rate of flow
US3701280Mar 18, 1970Oct 31, 1972Daniel Ind IncMethod and apparatus for determining the supercompressibility factor of natural gas
US3705516Sep 30, 1971Dec 12, 1972Northrop CorpMethod and apparatus for testing the condition of a machine
US3981836Sep 3, 1971Sep 21, 1976Dan River Inc.Yarn sizes, sizing treatments and resulting sized yarns
US4058275Dec 28, 1970Nov 15, 1977The United States Of America As Represented By The Secretary Of The NavyLow frequency passive guidance method
US4099413Jun 13, 1977Jul 11, 1978Yokogawa Electric Works, Ltd.Thermal noise thermometer
US4322976Apr 4, 1980Apr 6, 1982Ird Mechanalysis, Inc.Mechanical vibration analyzer
US4337516Jun 26, 1980Jun 29, 1982United Technologies CorporationSensor fault detection by activity monitoring
US4408285Feb 2, 1981Oct 4, 1983Ird Mechanalysis, Inc.Vibration analyzing apparatus and method
US4425798Mar 13, 1981Jan 17, 1984Kawasaki Steel CorporationApparatus for diagnosing abnormalities in rotating machines
US4435770Mar 19, 1981Mar 6, 1984Hitachi, Ltd.Vibration diagnosing method and apparatus for a rotary machine
US4493042Feb 19, 1982Jan 8, 1985Mitsubishi Denki Kabushiki KaishaBearing failure judging apparatus
US4517468Apr 30, 1984May 14, 1985Westinghouse Electric Corp.Diagnostic system and method
US4527271Aug 17, 1982Jul 2, 1985The Foxboro CompanyProcess control system with improved fault isolation
US4530234Jun 30, 1983Jul 23, 1985Mobil Oil CorporationMethod and system for measuring properties of fluids
US4607325Mar 30, 1984Aug 19, 1986Honeywell Inc.Discontinuous optimization procedure modelling the run-idle status of plural process components
US4635214Jun 29, 1984Jan 6, 1987Fujitsu LimitedFailure diagnostic processing system
US4642782Jul 31, 1984Feb 10, 1987Westinghouse Electric Corp.Rule based diagnostic system with dynamic alteration capability
US4644478Sep 13, 1983Feb 17, 1987International Business Machines Corp.Monitoring and alarm system for custom applications
US4644749Mar 21, 1983Feb 24, 1987Sperry CorporationPhase locked looped controller for motordrivers
US4649515Jul 1, 1986Mar 10, 1987Westinghouse Electric Corp.Methods and apparatus for system fault diagnosis and control
US4657179Dec 26, 1984Apr 14, 1987Honeywell Inc.Distributed environmental/load control system
US4683542Jul 11, 1984Jul 28, 1987Mitsubishi Denki Kabushiki KaishaVibration monitoring apparatus
US4707796Aug 13, 1986Nov 17, 1987Calabro Salvatore RReliability and maintainability indicator
US4734873Jul 18, 1986Mar 29, 1988Honeywell Inc.Method of digital process variable transmitter calibration and a process variable transmitter system utilizing the same
US4758964Apr 25, 1986Jul 19, 1988Fried. Krupp Gesellschaft Mit Beschrankter HaftungMethod and apparatus for monitoring machine parts
US4763243Jun 21, 1984Aug 9, 1988Honeywell Bull Inc.Resilient bus system
US4764862Mar 28, 1985Aug 16, 1988Honeywell Bull Inc.Resilient bus system
US4770543Nov 13, 1986Sep 13, 1988Daimer-Benz AktiengesellschaftDevice in a motor vehicle for indicating the outside temperature
US4777585Feb 3, 1986Oct 11, 1988Hitachi, Ltd.Analogical inference method and apparatus for a control system
US4819233Apr 8, 1987Apr 4, 1989Westinghouse Electric Corp.Verification of computer software
US4831564Oct 22, 1987May 16, 1989Suga Test Instruments Co., Ltd.Apparatus for estimating and displaying remainder of lifetime of xenon lamps
US4843557Jan 6, 1987Jun 27, 1989Nippondenso Co., Ltd.Overall diagnosis apparatus for vehicle-mounted control devices
US4873655Aug 21, 1987Oct 10, 1989Board Of Regents, The University Of Texas SystemSensor conditioning method and apparatus
US4885694Apr 29, 1987Dec 5, 1989Honeywell Inc.Automated building control design system
US4885707Feb 19, 1987Dec 5, 1989Dli CorporationVibration data collecting and processing apparatus and method
US4907167Sep 30, 1987Mar 6, 1990E. I. Du Pont De Nemours And CompanyProcess control system with action logging
US4910691Sep 30, 1987Mar 20, 1990E.I. Du Pont De Nemours & Co.Process control system with multiple module sequence options
US4922412Feb 21, 1989May 1, 1990The Babcock & Wilcox CompanyApparatus and method using adaptive gain scheduling
US4924418Aug 23, 1988May 8, 1990Dickey-John CorporationUniversal monitor
US4934196Jun 2, 1989Jun 19, 1990Micro Motion, Inc.Coriolis mass flow rate meter having a substantially increased noise immunity
US4942514Nov 9, 1988Jul 17, 1990Hitachi, Ltd.Process monitoring and control system and method of process monitoring and control
US4944035Jun 24, 1988Jul 24, 1990Honeywell Inc.Measurement of thermal conductivity and specific heat
US4956793Jun 24, 1988Sep 11, 1990Honeywell Inc.Method and apparatus for measuring the density of fluids
US4964125Aug 19, 1988Oct 16, 1990Hughes Aircraft CompanyMethod and apparatus for diagnosing faults
US4965742Sep 30, 1987Oct 23, 1990E. I. Du Pont De Nemours And CompanyProcess control system with on-line reconfigurable modules
US4980844May 27, 1988Dec 25, 1990Victor DemjanenkoMethod and apparatus for diagnosing the state of a machine
US4992965Nov 30, 1988Feb 12, 1991Eftag-Entstaubungs- Und Fordertechnik AgCircuit arrangement for the evaluation of a signal produced by a semiconductor gas sensor
US5005142Jul 24, 1989Apr 2, 1991Westinghouse Electric Corp.Smart sensor system for diagnostic monitoring
US5006992Sep 30, 1987Apr 9, 1991Du Pont De Nemours And CompanyProcess control system with reconfigurable expert rules and control modules
US5008810Sep 29, 1988Apr 16, 1991Process Modeling Investment Corp.System for displaying different subsets of screen views, entering different amount of information, and determining correctness of input dependent upon current user input
US5015934Sep 25, 1989May 14, 1991Honeywell Inc.Apparatus and method for minimizing limit cycle using complementary filtering techniques
US5018215Mar 23, 1990May 21, 1991Honeywell Inc.Knowledge and model based adaptive signal processor
US5043862Apr 6, 1989Aug 27, 1991Hitachi, Ltd.Method and apparatus of automatically setting PID constants
US5043863May 2, 1989Aug 27, 1991The Foxboro CompanyMultivariable adaptive feedforward controller
US5050095Jan 10, 1990Sep 17, 1991Honeywell Inc.Neural network auto-associative memory with two rules for varying the weights
US5053815Apr 9, 1990Oct 1, 1991Eastman Kodak CompanyReproduction apparatus having real time statistical process control
US5070458Mar 31, 1989Dec 3, 1991Honeywell Inc.Method of analyzing and predicting both airplane and engine performance characteristics
US5081598Feb 21, 1989Jan 14, 1992Westinghouse Electric Corp.Method for associating text in automatic diagnostic system to produce recommended actions automatically
US5089978Feb 9, 1990Feb 18, 1992Westinghouse Electric Corp.Automatic plant state diagnosis system including a display selection system for selecting displays responsive to the diagnosis
US5089984May 15, 1989Feb 18, 1992Allen-Bradley Company, Inc.Adaptive alarm controller changes multiple inputs to industrial controller in order for state word to conform with stored state word
US5094107Aug 21, 1990Mar 10, 1992The Minster Machine CompanyPress vibration severity/reliability monitoring system and method
US5098197Jan 30, 1989Mar 24, 1992The United States Of America As Represented By The United States Department Of EnergyOptical Johnson noise thermometry
US5099436Nov 3, 1988Mar 24, 1992Allied-Signal Inc.Methods and apparatus for performing system fault diagnosis
US5103409Jan 3, 1990Apr 7, 1992Hitachi, Ltd.Field measuring instrument and its abnormality managing method
US5111531Jan 8, 1990May 5, 1992Automation Technology, Inc.Process control using neural network
US5121467Aug 3, 1990Jun 9, 1992E.I. Du Pont De Nemours & Co., Inc.Neural network/expert system process control system and method
US5122976Mar 12, 1990Jun 16, 1992Westinghouse Electric Corp.Method and apparatus for remotely controlling sensor processing algorithms to expert sensor diagnoses
US5130936Sep 14, 1990Jul 14, 1992Arinc Research CorporationMethod and apparatus for diagnostic testing including a neural network for determining testing sufficiency
US5134574Feb 27, 1990Jul 28, 1992The Foxboro CompanyPerformance control apparatus and method in a processing plant
US5140530Mar 28, 1989Aug 18, 1992Honeywell Inc.Genetic algorithm synthesis of neural networks
US5142612Aug 3, 1990Aug 25, 1992E. I. Du Pont De Nemours & Co. (Inc.)Computer neural network supervisory process control system and method
US5148378Nov 19, 1990Sep 15, 1992Omron CorporationSensor controller system
US5161013Apr 8, 1991Nov 3, 1992Honeywell Inc.Data projection system with compensation for nonplanar screen
US5167009Aug 3, 1990Nov 24, 1992E. I. Du Pont De Nemours & Co. (Inc.)On-line process control neural network using data pointers
US5175678Aug 15, 1990Dec 29, 1992Elsag International B.V.Method and procedure for neural control of dynamic processes
US5187674Dec 28, 1989Feb 16, 1993Honeywell Inc.For determining fuel gas pressure
US5193143Nov 7, 1989Mar 9, 1993Honeywell Inc.Problem state monitoring
US5197114Aug 3, 1990Mar 23, 1993E. I. Du Pont De Nemours & Co., Inc.Computer neural network regulatory process control system and method
US5197328Jan 9, 1992Mar 30, 1993Fisher Controls International, Inc.Diagnostic apparatus and method for fluid control valves
US5200028Aug 7, 1991Apr 6, 1993Sony CorporationUsing two gaseous mixtures having different ratios of hydrogen bromide gas and a fluorine radical-donating gas; precise detection of end-point
US5200958Sep 28, 1990Apr 6, 1993Xerox CorporationMethod and apparatus for recording and diagnosing faults in an electronic reprographic printing system
US5210704Oct 2, 1990May 11, 1993Technology International IncorporatedSystem for prognosis and diagnostics of failure and wearout monitoring and for prediction of life expectancy of helicopter gearboxes and other rotating equipment
US5212765Aug 3, 1990May 18, 1993E. I. Du Pont De Nemours & Co., Inc.On-line training neural network system for process control
US5214582Jan 30, 1991May 25, 1993Edge Diagnostic SystemsInteractive diagnostic system for an automotive vehicle, and method
US5224203Jul 22, 1992Jun 29, 1993E. I. Du Pont De Nemours & Co., Inc.On-line process control neural network using data pointers
US5228780Oct 30, 1992Jul 20, 1993Martin Marietta Energy Systems, Inc.Dual-mode self-validating resistance/Johnson noise thermometer system
US5235527Nov 10, 1992Aug 10, 1993Toyota Jidosha Kabushiki KaishaMethod for diagnosing abnormality of sensor
US5251151Dec 24, 1990Oct 5, 1993Research Foundation Of State Univ. Of N.Y.From a vibrational signal
US5265031Nov 26, 1990Nov 23, 1993Praxair Technology, Inc.Diagnostic gas monitoring process utilizing an expert system
US5265222Nov 23, 1990Nov 23, 1993Hitachi, Ltd.Symbolization apparatus and process control system and control support system using the same apparatus
US5274572Mar 6, 1990Dec 28, 1993Schlumberger Technology CorporationMethod and apparatus for knowledge-based signal monitoring and analysis
US5282131Jan 21, 1992Jan 25, 1994Brown And Root Industrial Services, Inc.Control system for controlling a pulp washing system using a neural network controller
US5282261Aug 3, 1990Jan 25, 1994E. I. Du Pont De Nemours And Co., Inc.Neural network process measurement and control
US5291190Mar 28, 1991Mar 1, 1994Combustion Engineering, Inc.Operator interface for plant component control system
US5293585Sep 17, 1992Mar 8, 1994Kabushiki Kaisha ToshibaIndustrial expert system
US5301101Apr 14, 1993Apr 5, 1994Honeywell Inc.Receding horizon based adaptive control having means for minimizing operating costs
US20020161940 *Feb 28, 2002Oct 31, 2002Evren EryurekCreation and display of indices within a process plant
US20040186927 *Mar 18, 2003Sep 23, 2004Evren EryurekAsset optimization reporting in a process plant
USRE29383Jan 31, 1977Sep 6, 1977Process Systems, Inc.Digital fluid flow rate measurement or control system
Non-Patent Citations
Reference
1"Components of GE Predictor(TM) Services," GE Industrial Systems, available at http://www.geindustrial.com/cwc/services?id=74 on Jul. 18, 2002.
2"Customer Benefits," GE Industrial Systems, available at http://www.geindustrial.com/cwc/services?id=75 on Jul. 18, 2002.
3"Customer Impact," GE Industrial Systems, available at http://www.geindustrial.com/cwc/services?id=73 on Jul. 18, 2002.
4"Electrical Equipment Coverage," GE Industrial Systems, available at http://www.geindustrial.com/cwc/services?id=72 on Jul. 18, 2002.
5"GE Predictor(TM) Services: GE Predictor Services Overview," GE Industrial Systems, available at http://www.geindustrial.com/cwc/services?id=71 on Jul. 18, 2002.
6"Status Signals of Field Instruments," NAMUR Recommendation, NA 64, Feb. 1, 2001, pp. 1-8.
7dotnet.za.net, "Web Services-A Guide for Business and IT Managers (Sep. 23, 2001)", (Copyright 2001), www.dotnet.za.net.
8EPan Examination Report, EP 02717514.0, dated Jun. 29, 2004.
9EPan Examination Report, EP 02723319.6, dated Jul. 1, 2004.
10Examination Report under Section 18(3) issued in GB 0308687.9 by the United Kingdom Patent Office on Mar. 11, 2005.
11First Office Action issued in Chinese Application No. 02122060.3 on Feb. 4, 2005.
12First Office Action issued in Chinese Application No. 02805785.6 on Nov. 11, 2005.
13First Office Action issued in Chinese Application No. 02805854.2 on Nov. 11, 2005.
14Great Britain Examination Report under Section 18(3) issued Dec. 17, 2003 in Application No. GB 0126490.2.
15Great Britain Examination Report under Section 18(3) issued on Sep. 16, 2004 in Application No. GB 0212610.0.
16Great Britain Search Report under Section 17 performed on Dec. 11, 2002 in Application No. GB 0212610.0.
17International Preliminary Examination Report issued in PCT/US02/05874, EPan Patent Office, mailed Feb. 3, 2003.
18International Preliminary Examination Report issued in PCT/US02/15901, EPan Patent Office, mailed Sep. 10, 2003.
19International Preliminary Examination Report issued in PCT/US02/16033, EPan Patent Office, mailed Jun. 17, 2003.
20International Search Report for International Application No. PCT/US2006/029923 dated Nov. 21, 2006.
21International Search Report for PCT/US02/15901, mailed Jun. 17, 2003.
22International Search Report for PCT/US02/16033 dated Sep. 16, 2003.
23International Search Report for PCT/US04/004939, issued Sep. 8, 1994.
24International Search Report issued in PCT/US02/06577, EPan Patent Office, mailed Nov. 13, 2002.
25International Search Report of PCT/US02/05874, issued Nov. 13, 2002.
26Kalkhoff, W. "Agent-Oriented Robot Task Transformation," Proceeding of the International Symposium on Intelligent Control, IEEE, pp. 242-247 (Aug. 27, 1995).
27Lighthammer Illuminator(TM) Manufacturing Intelligence Brochure "Now you can see all your manufacturing information from a single interface-in real-time, from anywhere."
28Lighthammer Software Development, "Illuminator(TM) The 1<SUP>st </SUP>Plant Information Portal'(TM)" (Copyright 1999).
29Mazeda et al., "Supervision and Optimised Process Control in Sugar Beet Factories,"Centre of Sugar Technology, Spain from www.univreims.fr/externes/avh10mazaeda.pdf.
30Search Report under Section 17 (5) issued by Great Britain Patent Office, dated Jun. 11, 2002 in Application No. GB 0126490.2 (UK 2083258).
31Search Report under Section 17 (5) issued in GB 0308687.3 by the United Kingdom Patent Office on Aug. 29, 2003.
32Search Report under Section 17(5) issued in GB 0416908.2 application by the United Kingdom Patent Office, dated Oct. 13, 2004.
33Systinet, "Introduction to Web Services", (Copyright 2001, 2002), www.systinet.com.
34Web Services Architect, "What are Web Services", www.webservicesarchitect.com.
35Written Opinion for International Application No. PCT/US2006/029923 dated Nov. 21, 2006.
36Written Opinion issued in PCT/US02/05874, EPan Patent Office, mailed Nov. 13, 2002.
37Written Opinion issued in PCT/US02/15901, EPan Patent Office, mailed Jul. 16, 2003.
38Written Opinion issued in PCT/US02/16033, EPan Patent Office, mailed Jul. 21, 2003.
39Written Opinion of the International Searching Authority issued in PCT/US04/004939, mailed Sep. 29, 2004.
40Zolera Systems, "A Brief Guide to Web Services Protocols" (Copyright 2001), www.zolera.com.
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US8659415Jul 15, 2011Feb 25, 2014General Electric CompanyAlarm management
US20100076800 *Jul 28, 2009Mar 25, 2010Yokogawa Electric CorporationMethod and system for monitoring plant assets
US20110071655 *Feb 23, 2009Mar 24, 2011Guido SteinhauerApparatus and Method for Projecting Field Devices of a Technical System
Classifications
U.S. Classification702/182, 714/E11.02, 702/188, 702/181, 700/108, 702/187, 702/184, 702/185, 702/183, 702/186
International ClassificationG06F15/00
Cooperative ClassificationG06F3/0482, G06F11/008, G05B2219/32286
European ClassificationG06F3/0482, G06F11/00M
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